Abstract: A deployment manager executing in a distributed computing environment generates a user behavior analytics (UBA) deployment to process structured event data. The deployment manager configures a streaming cluster to perform streaming processing on real-time data and configures a batch cluster to perform batch processing on aggregated data. A configuration manager executing in the distributed computing environment interoperates with the deployment manager to update the UBA deployment with user-provided code and configurations that define streaming and batch models, among other things. In this manner, the deployment manager provides a scalable UBA deployment that can be customized, via the configuration manager, by a user.

Abstract: A deployment manager executing in a distributed computing environment generates a user behavior analytics (UBA) deployment to process structured event data. The deployment manager configures a streaming cluster to perform streaming processing on real-time data and configures a batch cluster to perform batch processing on aggregated data. A configuration manager executing in the distributed computing environment interoperates with the deployment manager to update the UBA deployment with user-provided code and configurations that define streaming and batch models, among other things. In this manner, the deployment manager provides a scalable UBA deployment that can be customized, via the configuration manager, by a user.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A deployment manager executing in a distributed computing environment generates a user behavior analytics (UBA) deployment to process structured event data. The deployment manager configures a streaming cluster to perform streaming processing on real-time data and configures a batch cluster to perform batch processing on aggregated data. A configuration manager executing in the distributed computing environment interoperates with the deployment manager to update the UBA deployment with user-provided code and configurations that define streaming and batch models, among other things. In this manner, the deployment manager provides a scalable UBA deployment that can be customized, via the configuration manager, by a user.

Abstract: A deployment manager executing in a distributed computing environment generates a user behavior analytics (UBA) deployment to process structured event data. The deployment manager configures a streaming cluster to perform streaming processing on real-time data and configures a batch cluster to perform batch processing on aggregated data. A configuration manager executing in the distributed computing environment interoperates with the deployment manager to update the UBA deployment with user-provided code and configurations that define streaming and batch models, among other things. In this manner, the deployment manager provides a scalable UBA deployment that can be customized, via the configuration manager, by a user.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

Abstract: A deployment manager executing in a distributed computing environment generates a user behavior analytics (UBA) deployment to process structured event data. The deployment manager configures a streaming cluster to perform streaming processing on real-time data and configures a batch cluster to perform batch processing on aggregated data. A configuration manager executing in the distributed computing environment interoperates with the deployment manager to update the UBA deployment with user-provided code and configurations that define streaming and batch models, among other things. In this manner, the deployment manager provides a scalable UBA deployment that can be customized, via the configuration manager, by a user.

Abstract: A deployment manager executing in a distributed computing environment generates a user behavior analytics (UBA) deployment to process structured event data. The deployment manager configures a streaming cluster to perform streaming processing on real-time data and configures a batch cluster to perform batch processing on aggregated data. A configuration manager executing in the distributed computing environment interoperates with the deployment manager to update the UBA deployment with user-provided code and configurations that define streaming and batch models, among other things. In this manner, the deployment manager provides a scalable UBA deployment that can be customized, via the configuration manager, by a user.

Abstract: A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.